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environment who will supervise the PhD and collaborating with the rest of the Doctoral Network fellows. Where to apply Website https://cv.newton-6g.eu/ Requirements Research FieldEngineering » Electrical
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Previous experience in protein biochemistry, LC/MS based mass spectrometry Previous experience in handling omics data analysis using software Experience in R and python is a plus but not mandatory Good
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development from spatial transcriptomics data. Activities : – design of a new mathematical method – monitoring and study of publications relevant to the field – programming/coding in Python (Pytorch
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 18 days ago
Website https://jobs.inria.fr/public/classic/en/offres/2026-09839 Requirements Skills/Qualifications Strong mathematical background. Knowledge in numerical optimization is a plus. Good programming skills in
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in C/C++ or Python. Knowledge of Linux (ubuntu), ROS 1 and/or 2, Gazebo and/or pybullet, Docker, git, Latex are a plus. Knowledge of SLAM, pose estimation, UWB, IMUs, VIO, LIO are a plus. Hands on
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, and AI, with a strong methodological focus. Where to apply Website https://www.academictransfer.com/en/jobs/359346/phd-position-large-language-mod… Requirements Specific Requirements We are looking
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science, oceanography, physics, environmental science, or a related field • Strong skills in scientific programming (Python, Fortran, or similar) • Interest in Earth system modelling and climate science
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This doctoral position is part of GRAIL (“Gamma Radiation from the Atmosphere for Investigation and Learning”), a prestigious Horizon Europe Marie Skłodowska-Curie Actions Doctoral Network (MSCA-DN): https
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presentations and draft sections of research papers Location: Department of Economics, Harvard University, Cambridge, MA Supervisor: Professor Gita Gopinath, website: https://gopinath.scholars.harvard.edu
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experiment on a metric-scale concrete wall, using the multi-physics NDE probe integrated onto drone platforms. Expected Results A Python-based multi-physics Maching Learning framework for NDE characterization